Denoising Diffusion Probabilistic Models (DDPM) [1]} combine generative models based on score matching and neural Diffusion Probabilistic Models into a single model. Similarly, in [2]}, [3]} a generative neural diffusion process based on score matching was applied to speech generation. These models achieve state-of-the-art results for speech generation, and show superior results over well-established methods, such as Wavernn [4]}, Wavenet [5]}, and GAN-TTS [6]}.
